Abstract
Reliability analysis of large power networks requires accurate aggregate models of low voltage (LV) networks to allow for reasonable calculation complexity and to prevent long computational times. However, commonly used lumped load models neglect the differences in spatial distribution of demand, type of phase-connection of served customers and implemented protection system components (e.g., single-pole vs three-pole). This paper proposes a novel use of state enumeration (SE) and Monte Carlo simulation (MCS) techniques to formulate more accurate LV network reliability equivalents. The combined SE and MCS method is illustrated using a generic suburban LV test network, which is realistically represented by a reduced number of system states. This approach allows for a much faster and more accurate reliability assessments, where further reduction of system states results in a single-component equivalent reliability model with the same unavailability as the original LV network. Both mean values and probability distributions of standard reliability indices are calculated, where errors associated with the use of single-line models, as opposed to more detailed three-phase models, are quantified.

Abstract
This paper presents a reliability-based approach for the design and deployment of an energy management system (EMS) by using 'smart' applications, such as energy storage (ES), to control battery power output in residential dwellings, and thus improve distribution-network reliability performance. The state of charge (SOC) of the battery system is designed based on time-varying electricity tariff, load demand and solar photovoltaic (PV) generation data to investigate a realistic test-case scenario. Additionally, a typical MV/LV urban distribution system is fully modelled and scripted to investigate the potential benefits that 'smart' interventions can offer to customers' quality of power supply. In this research, Monte-Carlo simulation method is further developed to include the time-variation of electricity demand profiles and failure rates of network components. Accordingly, the reliability-based effects from SOC variation in batteries are compared with an uncontrolled microgeneration (MG) scenario, by using different PV penetration levels to justify the value of control. The benefits are assessed through standard reliability indices measuring frequency and duration of power interruptions and most importantly, the energy not supplied to customers during sustained interruptions.

Abstract
This paper, which is part one of a two-part series, presents a general methodology for reducing system complexity by calculating the electrical and reliability equivalent models of low and medium voltage distribution networks. These equivalent models help to reduce calculation times while preserving the accuracy assessment of power system reliability performance. The analysis is applied to typical UK distribution systems, which supply four generic load sectors with different networks and demand compositions (residential, commercial and industrial). This approach allows for a direct correlation between reliability performance and network characteristics, while assessing the most representative aggregate values of failure rates and repair times of power components at each load sector. These are used in the Part 2 paper for assessing the potential benefits of energy storage and demand-side resources on the reliability performance of different generic distribution networks. © 2013 IEEE.

Abstract
This paper, which is the second part of a two-part series, considers the influence of distributed energy resource functionalities on reliability performance of active networks. The reliability and network equivalent models defined in the Part 1 paper are used to assess the potential improvements that different demand-side management and energy storage schemes will have on the frequency and duration of customer interruptions. Particular attention is given to energy-related reliability indices which measure the energy and power not supplied to residential and commercial customers. A new theoretical interruption model is also introduced for a more accurate correlation between the different low-voltage and medium-voltage demand profiles and the time when both long and short interruptions are more likely to occur. © 2013 IEEE.

Abstract
This paper applies optimal power flow (OPF) to evaluate and maximize network benefits of demand-side management (DSM). The benefits are quantified in terms of the ability of demand-responsive loads to relieve upstream network constraints and provide ancillary services, such as operating reserve. The study incorporates detailed information on the load structure and composition, and allows the potential network benefits, which could be obtained through management of different load types, to be quantified and compared. It is demonstrated that the actual network location of demand-manageable load has an important influence on the effectiveness of the applied DSM scheme, since the characteristics of the loads and their interconnecting networks vary from one location to another. Consequently, some network locations are more favorable for implementation of DSM, and OPF can be applied to determine the optimal allocation of demand-side resources. The effectiveness of the presented approach is assessed using a time-sequential OPF applied to typical radial and meshed U.K. distribution networks. The results of the analysis suggest that network operators could not just participate in, but also encourage and add value to the implementation of specific DSM schemes at the optimum network locations in order to maximize the total benefit from DSM. © 2014 IEEE.

Abstract
This study introduces a new theoretical interruption model for assessing more accurately the moment in time when interruptions of electricity customers are likely to occur. Recordings of short and long interruptions from two power supply systems are analysed and the similarity between their patterns is identified and then used to introduce a general interruption probability distribution model, defined in stages as multi-zone theoretical curves. The effectiveness of the proposed theoretical interruption model is firstly verified for a basic test system supplying an aggregate load point whose power profiles (residential, commercial, industrial and mixed load) are engaged in assessing the energy not supplied, and afterwards for a typical UK power supply system consisting of about 15 000 electricity customers. The results show that a correct representation of the moment of interruption performed with the proposed model leads to completely different results than those obtained based on the conventional assumption that the time when interruption occurs is given by a known probability distribution. Moreover, comparisons against reported figures of reliability indices determine the most suitable probability distribution that shall be used to model the initial conditions of the Monte Carlo simulation and accompany the proposed theoretical model throughout the simulation process. © The Institution of Engineering and Technology 2014.